The role of information exchange

In this research, information exchange refers to exchange of point of sales information and inventory status from downstream to upstream members, and all other information that may impact on sales (for example - promotional sales) exchanged among upstream and downstream members for the purpose of organisational planning (both long range and short range planning), forecasting, production and replenishment.

The literature articles on supply chain information exchange focuses mainly on two areas. One is production and replenishment, and the other is forecasting and planning. Either cost reduction or inventory control is the primary motive of these supply chain collaborations (Chen, 1998; Cachon and Fisher, 2000; Kulp et al., 2004). This section considers articles

dealing with supply chain collaboration and information exchange for the purpose of improved forecast accuracy and timely replenishment.

In contrast to traditional supply chain practices, today‘s supply chain management is more transparent to supply chain operators. Healthy collaborative arrangements among supply chain partners proved to be a successful integral part of many world-class businesses such as Wal-Mart, Sara Lee, Nabisco etc (Lee, 2002). Following the greatly successful adoption of CPFR in the US, many companies around the globe have experimented with collaborative partnerships in their supply chain (Seifert, 2003). Transparent information sharing in supply chain collaboration hopes to reduce uncertainty and avoid excess inventory (Holweg et al., 2005; Chen et al., 2000).

Initially at the inception of CPFR, understanding of the collaboration process and the framework to collaborate were considered the two basic requirements for a collaborative supply chain (Barratt and Oliveira, 2001). In a later stage, information sharing was recognised as one of the key elements for the success of the collaboration (Seifert, 2003). Li and Wang (2007) have asserted that the benefit of information sharing is dependent on two factors: one is content and another is proper use of information (Lee and Whang, 1999, 2001; Lee et al., 2000; Raghunathan, 2001). Distorted information and inefficient use of available data will lead to excess inventory in each level of the supply chain. Hence, it may be important for the companies under collaboration to decide on what information to exchange in order to reduce cost or inventory, to create more accurate demand forecasts, to make production flexible, and to achieve timely replenishments.

Sharing of demand information with upstream members can help reducing the manufactures‘ supply chain cost (Raghunathan, 1999). Knowledge of demand information also reduces the inventory cost of both supplier and customer (Gavirneni, et al., 1999, Lee, et al., 2000; Graves, 1999). Sharing demand information along with current inventory status facilitates achieving reductions in inventory cost (Chen 1998; Cachon and Fisher, 2000).

Depending upon the forecasting capabilities (technology and manpower) of the parties involved, the benefit of information sharing will also range from basic inventory reduction to higher profit earning. The manufacturer could reduce the variance in demand forecast if readily available historical order data is being used capably (Raghunathan, 2001).

POS data and market-data-sharing are found influential in achieving forecast accuracy in Chang et al. (2007)‘s ‗augmented CPFR‘ model. A more detailed discussion on the value of information sharing in supply chains is given in Li et al. (2005). Sanders and Premus (2005) have attempted to model the relationship between firm IT capability, collaboration and performance. However, the authors have not discussed information sharing and forecasting in detail.

Most of the above discussed literature lists the benefits of exchanging information either of point of sale data or inventory data but not any other information. Recognising the type of information to be shared among supply chain members to build-in more visibility is a big challenge in achieving collaboration (Barratt and Oliveira, 2001). Ryu et al. (2009) have presented a simulation study on the evaluation of supply chain information sharing. They have compared the value of exchanging short term forecasts and long term forecasts among SC players. Under high demand variability, long term forecasts performed better than short

term forecasts. Under low demand variability, short term forecasts performed better than long term forecasts. Using store level SKU data, Ali et al. (2009) have found that simple time series forecasting will be appropriate for normal sales without promotions. They have suggested using advanced techniques for sophisticated input to improve forecast accuracy of promotional sales. See Table 2-4 for more literature on information sharing.

Table 2-4 Literature on information sharing

While most of the articles support sharing of POS data for reduction of cost or inventory, a very recent paper by Nakano (2009) has claimed that internal forecasting (with-in the firm) but not external collaborative forecasting (with other supply chain players) had significant impact on logistics and production performance. He has used survey data from the Japanese manufacturing sector to develop a structural equation model. However, his results have

Authors Information sharing Purpose

Bourland et al. (1996)

Inventory Minimising inventory cost

Cachon and Fisher (1997)

Historical data (no need to invest)

Decision on technology investment

Chen (1998) Demand and inventory Minimising total inventory cost

Gavireneni et al. (1999)

POS and Inventory Minimising inventory cost

Cachon and Fisher (2000)

Demand and inventory Minimising inventory cost throughout whole

supply chain

Lee et al.(2000) Demand information Minimising inventory cost

Raghunathan (2001) Order history

(no need to invest )

Decision on technology investment

Kulp et al. (2004) Demand information

(Asymmetric)

Improve supplier benefit Byrne and Heavey

(2006)

Inventory, sales, order status, sales forecast, production/ delivery schedule

Total supply chain cost saving

Chang et al.(2007) POS & market data Improve responsiveness to demand

fluctuations

Ketzenberg (2009) Demand, recovery yield,

capacity utilisation

Capacity utilisation showed more value than any other information in a capacitated closed loop supply chain.

Ryu et al. (2009) Demand information Study changes in inventory level and service

level

identified a positive relationship between internal forecasting and planning, and external (upstream/downstream) collaborative forecasting.

Information exchange among supply chain partners has been viewed as a tool of performance improvement in the supply chain (Cachon and Fisher, 2000; Byrne and Heavey, 2006; Lee et al., 2000). In this line, a special issue of the Management Science journal in 2004 on ‗marketing and operations management interfaces and coordination‘ has debated various issues in the fields of operations management and marketing having sales information as a main focus. In this special issue, Kulp et al. (2004) have related different forms of information and knowledge integration to evaluate the supply chain performance. Steckel et al. (2004) have questioned the importance of point of sale information (POS). The authors have argued that the POS information may distract decision making particularly if product demand is highly fluctuating. However, Aviv (2001; 2007) has supported sharing sales information and local forecasting between retailers and manufactures. Through mathematical models the author has confirmed that collaborative forecasting (CF) could improve the forecast accuracy of products with short lead times. In another study Aviv (2007) has also confirmed that CF could improve the overall performance of SC by about four percent. However, depending on other factors, such as explanatory power of the supply chain partners, the supply side agility, and the internal service rate, the performance improvement will differ (Aviv, 2007).

The quality of the information exchanged among the supply chain partners is another important factor that decides the performance. The overall supply chain performance has been shown to be higher with high quality information from supply chain partners (Forsuland and Jonsson, 2007; Zhao et al., 2002). But, obtaining high quality information

in the supply chain requires a high level of cooperation and trust among various players (Barratt and Oliveria, 2001; Fliedner, 2003). Good inter-organisational communication among various supply chain players is therefore necessary (Paulraj et al., 2008). This inter- organisational communication is vital especially during sales promotions.

In recent years, many retail outlets offer promotional sales in collaboration with manufacturers (Ailawadi et al., 2009). This initiates more collaborative action among various supply chain players. Knowing the demand information (POS information) and inventory levels at the retail outlets may help the supplier to replenish on time (Gavirneni, 1999; Cachon and Fisher, 2000). It has always been accepted that good forecasting will avoid stock outs and excess inventory. But, achieving good forecast accuracy in the presence of promotions is not an easy task because the buying behaviour of customers can be influenced by various factors (Sun, 2005).

This research will demonstrate the significant impact of collaborative forecasting in improving the accuracy of promotional sales by having demand information from other downstream supply chain partners.